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[资源] 【转贴】 GOOGLE强大的搜索功能揭密【已搜无重复】

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以下是该文中所介绍核心算法的摘要：
ABSTRACT
MapReduce is a programming model and an associated
implementation for processing and generating large
data sets. Users specify a map function that processes a
key/value pair to generate a set of intermediate key/value
pairs, and a reduce function that merges all intermediate
values associated with the same intermediate key. Many
real world tasks are expressible in this model, as shown
in the paper.
Programs written in this functional style are automatically
parallelized and executed on a large cluster of commodity
machines. The run-time system takes care of the
details of partitioning the input data, scheduling the program's
execution across a set of machines, handling machine
failures, and managing the required inter-machine
communication. This allows programmers without any
experience with parallel and distributed systems to easily
utilize the resources of a large distributed system.
Our implementation of MapReduce runs on a large
cluster of commodity machines and is highly scalable:
a typical MapReduce computation processes many terabytes
of data on thousands of machines. Programmers
nd the system easy to use: hundreds of MapReduce programs
have been implemented and upwards of one thousand
MapReduce jobs are executed on Google's clusters
every day.

[ Last edited by 幻影无痕 on 2007-8-9 at 14:02 ]

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